The backend of AI Lab is a RESTful API built using Django 5 and Django REST Framework, designed to serve as a multi-modal AI interaction platform. It enables users to chat with an AI assistant, generate images and voice messages based on text prompts, and upload custom image data for enhanced AI context—all via secure and scalable endpoints.

👉 You can see a description of the frontend here.

AI Lab integrates tightly with OpenAI’s GPT-4o model, utilizing both classic request-response flows and experimental real-time WebSocket-based messaging. For structured tool usage, the backend supports function-calling capabilities, allowing the AI to retrieve external data—such as stock prices—by triggering custom Python functions through OpenAI's tool calling interface.

The backend includes the following core features:

• Text-to-AI chat: Receives user questions (optionally with images) and returns concise AI-generated responses in a humorous tone.
• Image generation: Generates visual content from text prompts using OpenAI’s DALL·E APIs, downloads them securely, and returns accessible media links.
• Voice generation: Converts AI-generated messages into realistic MP3 audio files using OpenAI’s voice synthesis, returning media URLs for playback.
• Prompt image uploads: Users can upload multiple images which are processed and incorporated into AI prompt contexts.
• Image download endpoint: Provides direct access to previously generated images for offline use.

Files and media are handled securely using Django’s media storage system, with automatic filename sanitization and conflict resolution. All AI-generated content (text, images, voice) is stored under versioned and categorized directories to facilitate media reuse and auditing.

Error handling is robust and transparent, with clear error responses returned to the frontend in case of invalid prompts, failed downloads, or AI response issues. The system is structured to be extensible—new tools, AI models, and integrations can be easily added via service layer abstraction.

The backend is permissioned using AllowAny for public access endpoints, ideal for early experimentation and open integration. For production environments, it supports migration to more restrictive policies and user authentication mechanisms.

AI Lab’s backend is deployed in a scalable cloud environment, making it globally accessible and production-ready. With clear API design, clean code architecture, and multi-modal AI integration, it offers a powerful foundation for building next-generation AI-assisted applications.